Muaremi, Amir, Dr.

Amir Muaremi

ETH Zürich
Amir Muaremi
Institut f. Elektronik
ETZ H 95
Gloriastrasse 35
8092 Zürich

Phone: +41 44 632 05 44

Amir Muaremi obtained the BSc degree in Electrical Engineering from HSR Rapperswil in 2008 and the MSc degree in Electrical Engineering and Information Technology from ETH Zurich in 2010. He performed the Master Thesis in the Speech and Audio Processing (SAP) Group at Imperial College London.

Amir Muaremi joined the Wearable Computing Group at the Electronics Laboratory in January 2011 and completed the PhD in December 2014.

Since 2016, he is a postdoctoral research fellow in the Wearable Health Lab at Stanford University.

Research Interests

Research Projects

MONARCA - MONitoring, treAtment and pRediCtion of bipolAr Disorder Episodes

[Project homepage]


The European research project MONARCA aims on developing and validating mobile technologies for multi-parametric, long term monitoring of behavioural and physiological information relevant to bipolar disorder. It combines those solutions with an appropriate platform and a set of services into an innovative system for management, treatment, and self-treatment of the disease.

As part of MONARCA, the our contribution comprise three parts: (i) further development of existing sensor technology to measure physiological signals, (ii) implementation of algorithms for detecting user’s mental state on mobile platforms, and (iii) evaluation of sensor technology and algorithms in medical trials.

Continuous Monitoring of Stress during Daily Life

[Project homepage]


Work should be a source of health, pride, and happiness, in the sense of enhancing motivation and strengthening personal development. Healthy and motivated employees perform better and remain loyal to the company for a longer time. But, when the person constantly experiences high workload over a longer period of time and is not able to recover, then work may lead to prolonged negative effects and might cause serious illnesses like chronic stress disease.

In this project, we investigate new methods for assessing the stress experience of people, using features derived from smartphones and wearable sensors. In particular, we use information from audio, physical activity, and communication data collected during workday and bio-physiological data collected at night during sleep.

Monitoring Groups and Individuals during Hajj Pilgrimage

[Project homepage]


The Hajj pilgrimage to Makkah and Madinah is one of the biggest annual events in the world, where millions of people congregate for religious rituals over several days. The main challenge for organizers and participants is to ensure a smooth flow through the activities and a safe, healthy and spiritual journey during the pilgrimage. A deep knowledge of how the pilgrims behave during this event is a precondition for improving these issues.

In this work we use a proximity system to identify pilgrims social networks derived from smartphones and apply social network analysis to understanding aspects of pilgrimage. Moreover, through observing differences in bio-physiological responses of the subjects during prayers, we try to differentiate between different types of prayers.

Other Involvements


Student Projects


2015 2014 2013 2012 2011

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